Integration of online and offline control valve data

ABSTRACT

An integrated diagnostics system utilizes online and offline diagnostics techniques to evaluate control valves found in process plant environments. The integrated diagnostics system improves on existing diagnostic systems, which typically rely exclusively on online diagnostics or offline diagnostics.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/412,204, filed on Oct. 24, 2016, and titled “Integration ofOnline and Offline Control Valve Data,” the entire disclosure of whichis hereby expressly incorporated by reference herein.

TECHNICAL FIELD

The present disclosure generally relates to diagnostics for controlvalves, and, in particular, to integrated diagnostics systems andmethods that incorporate online and offline diagnostics to evaluatecontrol valves.

BACKGROUND

Process control systems, such as those used in chemical, petroleum orother process plants, typically include one or more process controllerscommunicatively coupled to at least one host or operator workstation andto one or more field devices via analog, digital, or combinedanalog/digital communication links.

The process controllers receive signals indicative of processmeasurements made by sensors and/or field devices and/or otherinformation pertaining to the field devices and execute a controllerapplication that runs, for example, different control modules that makeprocess control decisions, generate control signals based on thereceived information and coordinate with the control modules or blocksbeing performed in the field devices, such as HART®, Wireless HART®, andFOUNDATION® Fieldbus field devices. The control modules in thecontroller send the control signals over the communication lines orlinks to the field devices to thereby control the operation of at leasta portion of the process plant or system.

The field devices, which may be, for example, valves, valve positioners,switches, and transmitters (e.g., temperature, pressure, level and flowrate sensors), are located within the process environment and generallyperform physical or process control functions such as opening or closingvalves, measuring process parameters, etc. to control one or moreprocess executing within the process plant or system. Smart fielddevices, such as field devices conforming to the well-known Fieldbusprotocol may also perform control calculations, alarming functions, andother control functions commonly implemented within the controller.

Information from the field devices and the controller is usually madeavailable over a data highway to one or more other hardware devices,such as operator workstations, personal computers or computing devices,data historians, report generators, centralized databases, or othercentralized administrative computing devices that are typically placedin control rooms or other locations away from the harsher plantenvironment. Each of these hardware devices typically is centralizedacross the process plant or across a portion of the process plant. Thesehardware devices run applications that may, for example, enable anoperator to perform functions with respect to controlling a processand/or operating the process plant, such as changing settings of theprocess control routine, modifying the operation of the control moduleswithin the controllers or the field devices, viewing the current stateof the process, viewing alarms generated by field devices andcontrollers, simulating the operation of the process for the purpose oftraining personnel or testing the process control software, keeping andupdating a configuration database, etc. The data highway utilized by thehardware devices, controllers and field devices may include a wiredcommunication path, a wireless communication path, or a combination ofwired and wireless communication paths.

A particular set of process control devices used to achieve a particularcontrol objective (e.g., controlling an inlet valve to a tank based onone or more measured process parameters) may be referred to as a processcontrol loop. Furthermore, each valve or other device may, in turn,include an inner loop wherein, for example, a valve positioner controlsa valve actuator (which may be electric, pneumatic, or hydraulic innature) to move a control element, such as a valve plug, in response toa control signal and obtains feedback from a sensor, such as a positionsensor, to control movement of the valve plug. This inner loop issometimes called a servo loop.

In the case of a hydraulic valve actuator, the control element may movein response to changing fluid pressure on an actuator such as a springbiased diaphragm, which may be caused by a valve positioner respondingto a change in the command signal. For example, in one standard valvemechanism, a command signal with a magnitude varying in the range of 4to 20 mA (milliamperes) causes the valve positioner to alter the amountof fluid and thus, the fluid pressure, within a pressure chamber inproportion to the magnitude of the command signal. Changing fluidpressure in the pressure chamber causes the actuator (i.e., the springbased diaphragm in this example) to move, which causes the controlelement (e.g., a valve plug) to move. Accurate and precise controldepends on a known relationship between (i) a change in pressure exertedon the control element and (ii) the resulting travel of the controlelement (sometimes simply referred to as travel of the valve).

In some cases, the relationship between supplied pressure and controlelement travel changes due to wear and tear on the valve, changes inprocess conditions (e.g., temperature or pressure of material flowingthrough the valve itself), changes in atmospheric conditions, etc. Insome circumstances, the relationship between supplied pressure andcontrol element travel is dynamic over time, and thus must consistentlybe reevaluated to maintain high performance control.

Generally speaking, valves can be diagnosed using offline diagnostics oronline data. Performing offline diagnostics typically involves strokingthe valve through its entire range of travel while collectingdiagnostics data (e.g., data indicative of the relationship between thesupplied pressure and the travel of the valve). While offlinediagnostics often provide a comprehensive picture of the overallbehavior of a valve, these diagnostics may fail to capture valvebehavior similar to what would be found in a commissioned, operatingvalve. This failure to capture “real world” valve behavior can beattributed to the fact that the conditions may vary greatly from on-lineto off-line operation due to extreme temperature, pressure, or otherconditions. Rather than moving in a manner similar to what one wouldexpect to see in the field, the valve is typically taken through a fullrange of travel at a standardized, slow, and methodical pace. While thisslow pace removes various dynamics from valve behavior and makes iteasier to compare the valve to other similar valves for the purpose ofidentifying valve health metrics, it is not always helpful by itself indetermining whether the health of an operating valve has deterioratedover time. Moreover, even if offline diagnostics more closely capturedvalve behavior similar to that expected in online operation, offlinediagnostics require that the valve be taken out of service because it isnot likely that the valve can be taken through a full range of travelwhile simultaneously maintaining control of a process. Consequently, theprocess must often be halted for offline diagnostic testing of a valve,which can be costly in terms of lost material and profit. As a result,offline diagnostics testing is infrequent, and control valves often goyears without updating offline diagnostics, resulting in a situationwhere offline diagnostics results, which may be years old, fail toaccount for break-in and normal wear and tear.

Online diagnostics are typically considered less invasive than offlinediagnostics, as online diagnostics can be utilized in-situ (i.e., whilethe valve is in service). In short, during online diagnostics, the valveoperates in normal operating condition while diagnostics data iscollected. This has an advantage of not only maintaining normaloperation of the valve and process while diagnostics data is collected,but also of accounting for the effect process conditions (e.g.,temperature, pressure, etc.) have on the performance of the valve.Unfortunately, online diagnostic methods may also provide limitedbenefits. Because diagnostics data is only collected during normalonline operation, online diagnostics methods may fail to capturediagnostics data pertaining to rare or unexpected conditions. Forexample, many valves have a limited (e.g., 40%-60%) travel range duringtypical operation. As a result, online diagnostics may fail to capturediagnostics data regarding how the valve would respond to a command toadjust the valve to a position outside of this limited range.

SUMMARY

An integrated diagnostics system utilizes online and offline diagnosticstechniques to evaluate control valves found in process plantenvironments. In some instances, embodiments of the integrateddiagnostics system may utilize prognostics, predictive analytics, and/orother suitable analytics techniques. The integrated diagnostics systemimproves on existing diagnostic systems, which typically relyexclusively on online diagnostics or offline diagnostics.

In an embodiment, a method comprises any one or more of the following:(i) receiving, by one or more processors, offline diagnostics data for acontrol valve, the offline diagnostics data describing a response of thecontrol valve to a first control signal for a first range of travel whenthe control valve is not in service in a process plant; (ii) receiving,by the one or more processors, online diagnostics data for the controlvalve, the online diagnostics data describing a response of the controlvalve to a second control signal for a second range of travel when thecontrol valve is in service in the process plant; (iii) using theoffline diagnostics data and the online diagnostics data, generating adiagnostic metric indicative of at least one operational parameter ofthe control valve, by the one or more processors; and/or (iv) inresponse to determining that the diagnostic metric exceeds a thresholdvalue, generating an indication to be provided to an operator via a userinterface.

In an embodiment, a system comprises any one or more of the following: acontrol valve in a process plant; a plurality of sensors configured tomonitor the control valve; and/or an integrated diagnostics system,which may be communicatively connected to the plurality of sensors. Theintegrated diagnostics system may be configured to do any one or more ofthe following: (i) receive, via the plurality of sensors, offlinediagnostics data for the control valve, the offline diagnostics datadescribing a response of the control valve to a first control signal fora first range of travel when the control valve is not in service in theprocess plant; (ii) receive, via the plurality of sensors, onlinediagnostics data for the control valve, the online diagnostics datadescribing a response of the control valve to a second control signalfor a second range of travel when the control valve is in service in theprocess plant; (iii) generate, using the offline diagnostics data andthe online diagnostics data, a diagnostic metric indicative of at leastone operational parameter of the control valve; and/or (iv) generate, inresponse to determining that the diagnostic metric exceeds a thresholdvalue, an indication to be provided to an operator via a user interface.

In an embodiment, a method comprises any one or more of the following:(i) initiating an offline diagnostics procedure on a control valve in aprocess plant, wherein the control valve is controlled through a rangeof travel; (ii) collecting, during the offline diagnostics procedure,offline diagnostics data from a plurality of sensors monitoring thecontrol valve; (iii) calculating an offline response of the controlvalve utilizing the offline diagnostics data; (iv) collecting, duringonline operation of the control valve, online diagnostics data from theplurality of sensors monitoring the control valve; (v) calculating aplurality of online responses for the control valve utilizing the onlinediagnostics data; (vi) for each of the plurality of online responses,calculating a value for a response ratio relating the offline responseto one of the plurality of online responses; (vii) analyzing the valuesof the response ratio to determine a rate of change for the responseratio over time; and/or (viii) generating an indication to be providedto an operator via a user interface when the rate of change for theresponse ratio exceeds a threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

Each of the figures described below depicts one or more aspects of thedisclosed system(s) and/or method(s), according to an embodiment.Wherever possible, the Detailed Description refers to the referencenumerals included in the following figures.

FIG. 1 is a block diagram depicting an example process plant in which anintegrated diagnostics system may be implemented to diagnose and analyzeone or more control valves.

FIG. 2 is a conceptual block diagram depicting an integrated diagnosticssystem communicatively connected to a control valve, which may operatein the process plant of FIG. 1.

FIG. 3 illustrates an example digital valve controller capable ofcontrolling a valve and implementing diagnostics functions used by theintegrated diagnostics system.

FIG. 4 illustrates an example plot of actuator pressure versus valveposition for a typical sliding stem valve, generated by an integrateddiagnostics system performing online diagnostics.

FIG. 5 illustrates an example plot of actuator pressure versus valveposition, generated by an integrated diagnostics system performing anintegrated diagnostics analysis that utilizes both online and offlinediagnostics.

FIG. 6 is a flow chart depicting an example method of performing anintegrated diagnostics analysis, which can be implemented in theintegrated diagnostics system of FIG. 2.

DETAILED DESCRIPTION

Generally speaking, an integrated diagnostics system of this disclosureutilizes online and offline diagnostics data to evaluate parameters of acontrol valve operating in a process plant environment. Rather thanrelying exclusively on online diagnostics or offline diagnostics, theintegrated diagnostics system uses both types of data to more accuratelydetect such issues as deteriorating valve health, in a wider range ofcases. Moreover, the integrated diagnostics system operates in anon-intrusive manner and generally does not require that a valve betaken offline for testing.

For example, for a certain control valve the integrated diagnosticssystem can determine an offline “signature” (a characteristic responseof a process variable to a control signal) and one or more onlinesignatures, each of which may correspond to a full range of travel or apart of the range of travel. The integrated diagnostics system cancollect online operating data for the control valve and compare thecollected online operating data to the offline and online signatures.The integrated diagnostics system can select a diagnostic metric andcompare current values for the diagnostic metric to those found in theonline and offline signature. Examples of such metrics include the timerequired to move a valve a given amount in response to a given pressure,the rate at which valve changes for a given increase in pressure, etc.

Advantageously, the integrated diagnostics system can reduce the numberof false positives that the existing diagnostics systems relyingexclusively on online or offline diagnostics techniques are prone togenerate. Because the integrated diagnostics system can establish abaseline with an offline signature and also tracks recent behavior withan online signature, the integrated diagnostics system can establish arange of behavior that might be expected for a wide variety ofcircumstances. For example, a system relying only on online diagnosticsmay generate a false positive regarding the health of the valve when thevalve is operated outside of its normal routine (e.g., opening orclosing the valve to an atypical position at an atypical rate) simplybecause the system has little diagnostics data describing behavior ofthe valve outside of normal behavior. By contrast, the integrateddiagnostics system can compare the behavior of the valve to an offlinesignature to more accurately determine whether the behavior of the valverepresents a problem.

Below, section I describes, referencing FIG. 1, an example plantenvironment in which the integrated diagnostics system can beimplemented. Section II describes, referencing FIG. 2, an examplecontrol valve that may be diagnosed and analyzed by an integrateddiagnostics system. Section III describes, referencing FIG. 3, anexample valve controller that can implement diagnostics functions of anintegrated diagnostics system. Referencing FIGS. 4 and 5, section IVdescribes example plots that may be generated and analyzed by anintegrated diagnostics system. Section V describes, referencing FIG. 6,an example method of performing an integrated diagnostics analysis.Finally, Section VI includes additional remarks.

I. An Example Plant Environment in which an Integrated DiagnosticsSystem May be Implemented

FIG. 1 is a block diagram depicting an integrated diagnostics system 130that may be implemented to diagnose and analyze one or more controlvalves in a process plant 5 (sometimes referred to as a “process controlsystem” or “process control environment”). The process plant 5 isdescribed below, followed by a description of the integrated diagnosticssystem 130.

The process plant 5 includes one or more process controllers thatreceive signals indicative of process measurements made by fielddevices, process this information to implement a control routine, andgenerate control signals that are sent over wired or wireless processcontrol communication links or networks to other field devices tocontrol the operation of a process in the plant 5. Typically, at leastone field device performs a physical function (e.g., opening or closinga valve, increasing or decreasing a temperature, taking a measurement,sensing a condition, etc.) to control the operation of a process. Sometypes of field devices communicate with controllers by using I/Odevices. Process controllers, field devices, and I/O devices may bewired or wireless, and any number and combination of wired and wirelessprocess controllers, field devices and I/O devices may be included inthe process plant environment or system 5.

For example, FIG. 1 illustrates a process controller 11 that iscommunicatively connected to wired field devices 15-22 via input/output(I/O) cards 26 and 28, and that is communicatively connected to wirelessfield devices 40-46 via a wireless gateway 35 and a process control datahighway or backbone 10. One or more of the field devices 15-22 and 40-46may be a control valve. The process control data highway 10 may includeone or more wired and/or wireless communication links, and may beimplemented using any desired or suitable or communication protocol suchas, for example, an Ethernet protocol. In some configurations (notshown), the controller 11 may be communicatively connected to thewireless gateway 35 using one or more communications networks other thanthe backbone 10, such as by using any number of other wired or wirelesscommunication links that support one or more communication protocols,e.g., Wi-Fi or other IEEE 802.11 compliant wireless local area networkprotocol, mobile communication protocol (e.g., WiMAX, LTE, or otherITU-R compatible protocol), Bluetooth®, HART®, WirelessHART®, Profibus,FOUNDATION® Fieldbus, etc.

The controller 11, which may be, by way of example, the DeltaV™controller sold by Emerson Process Management, may operate to implementa batch process or a continuous process using at least some of the fielddevices 15-22 and 40-46. In an embodiment, in addition to beingcommunicatively connected to the process control data highway 10, thecontroller 11 is also communicatively connected to at least some of thefield devices 15-22 and 40-46 using any desired hardware and softwareassociated with, for example, standard 4-20 mA devices, I/O cards 26,28, and/or any smart communication protocol such as the FOUNDATION®Fieldbus protocol, the HART® protocol, the WirelessHART® protocol, etc.In FIG. 1, the controller 11, the field devices 15-22 and the I/O cards26, 28 are wired devices, and the field devices 40-46 are wireless fielddevices. Of course, the wired field devices 15-22 and wireless fielddevices 40-46 could conform to any other desired standard(s) orprotocols, such as any wired or wireless protocols, including anystandards or protocols developed in the future.

The process controller 11 of FIG. 1 includes a processor 30 thatimplements or oversees one or more process control routines 38 (e.g.,that are stored in a memory 32). The processor 30 is configured tocommunicate with the field devices 15-22 and 40-46 and with other nodescommunicatively connected to the controller 11. It should be noted thatany control routines or modules described herein may have parts thereofimplemented or executed by different controllers or other devices if sodesired. Likewise, the control routines or modules 38 described hereinwhich are to be implemented within the process control system 5 may takeany form, including software, firmware, hardware, etc. Control routinesmay be implemented in any desired software format, such as using objectoriented programming, ladder logic, sequential function charts, functionblock diagrams, or using any other software programming language ordesign paradigm. The control routines 38 may be stored in any desiredtype of memory 32, such as random access memory (RAM), or read onlymemory (ROM). Likewise, the control routines 38 may be hard-coded into,for example, one or more EPROMs, EEPROMs, application specificintegrated circuits (ASICs), or any other hardware or firmware elements.Thus, the controller 11 may be configured to implement a controlstrategy or control routine in any desired manner.

The controller 11 implements a control strategy using what are commonlyreferred to as function blocks, where each function block is an objector other part (e.g., a subroutine) of an overall control routine andoperates in conjunction with other function blocks (via communicationscalled links) to implement process control loops within the processcontrol system 5. Control based function blocks typically perform one ofan input function, such as that associated with a transmitter, a sensoror other process parameter measurement device, a control function, suchas that associated with a control routine that performs PID, fuzzylogic, etc. control, or an output function which controls the operationof some device, such as a valve, to perform some physical functionwithin the process control system 5. Of course, hybrid and other typesof function blocks exist. Function blocks may be stored in and executedby the controller 11, which is typically the case when these functionblocks are used for, or are associated with standard 4-20 mA devices andsome types of smart field devices such as HART® devices, or may bestored in and implemented by the field devices themselves, which can bethe case with FOUNDATION® Fieldbus devices. The controller 11 mayinclude one or more control routines 38 that may implement one or morecontrol loops which are performed by executing one or more of thefunction blocks.

The wired field devices 15-22 may be any types of devices, such assensors, valves, transmitters, positioners, etc., while the I/O cards 26and 28 may be any types of I/O devices conforming to any desiredcommunication or controller protocol. In FIG. 1, the field devices 15-®are standard 4-20 mA devices or HART® devices that communicate overanalog lines or combined analog and digital lines to the I/O card 26,while the field devices 19-22 are smart devices, such as FOUNDATION®Fieldbus field devices, that communicate over a digital bus to the I/Ocard 28 using a FOUNDATION® Fieldbus communications protocol. In someembodiments, though, at least some of the wired field devices 15, 16 and18-21 and/or at least some of the I/O cards 26, 28 additionally oralternatively communicate with the controller 11 using the processcontrol data highway 10 and/or by using other suitable control systemprotocols (e.g., Profibus, DeviceNet, Foundation Fieldbus, ControlNet,Modbus, HART, etc.).

In FIG. 1, the wireless field devices 40-46 communicate via a wirelessprocess control communication network 70 using a wireless protocol, suchas the WirelessHART® protocol. Such wireless field devices 40-46 maydirectly communicate with one or more other devices or nodes of thewireless network 70 that are also configured to communicate wirelessly(using the wireless protocol or another wireless protocol, for example).To communicate with one or more other nodes that are not configured tocommunicate wirelessly, the wireless field devices 40-46 may utilize awireless gateway 35 connected to the process control data highway 10 orto another process control communications network. The wireless gateway35 provides access to various wireless devices 40-58 of the wirelesscommunications network 70. In particular, the wireless gateway 35provides communicative coupling between the wireless devices 40-58, thewired devices 11-28, and/or other nodes or devices of the processcontrol plant 5. For example, the wireless gateway 35 may providecommunicative coupling by using the process control data highway 10and/or by using one or more other communications networks of the processplant 5.

Similar to the wired field devices 15-22, the wireless field devices40-46 of the wireless network 70 perform physical control functionswithin the process plant 5, e.g., opening or closing valves, or takingmeasurements of process parameters. The wireless field devices 40-46,however, are configured to communicate using the wireless protocol ofthe network 70. As such, the wireless field devices 40-46, the wirelessgateway 35, and other wireless nodes 52-58 of the wireless network 70are producers and consumers of wireless communication packets.

In some configurations of the process plant 5, the wireless network 70includes non-wireless devices. For example, in FIG. 1, a field device 48of FIG. 1 is a legacy 4-20 mA device and a field device 50 is a wiredHART® device. To communicate within the network 70, the field devices 48and 50 are connected to the wireless communications network 70 via awireless adaptor 52 a, 52 b. The wireless adaptors 52 a, 52 b support awireless protocol, such as WirelessHART, and may also support one ormore other communication protocols such as Foundation® Fieldbus,PROFIBUS, DeviceNet, etc. Additionally, in some configurations, thewireless network 70 includes one or more network access points 55 a, 55b, which may be separate physical devices in wired communication withthe wireless gateway 35 or may be provided with the wireless gateway 35as an integral device. The wireless network 70 may also include one ormore routers 58 to forward packets from one wireless device to anotherwireless device within the wireless communications network 70. In FIG.1, the wireless devices 40-46 and 52-58 communicate with each other andwith the wireless gateway 35 over wireless links 60 of the wirelesscommunications network 70, and/or via the process control data highway10.

As already noted, the process control system 5 includes an integrateddiagnostics system 130, which may execute on a host (sometimes referredto as a “server,” “computer,” etc.) 150 and may be communicativelycoupled to the data highway 10. The host 150 may be any suitablecomputing device, and may include a memory (not shown) storing thesystem 130 as one or more modules, applications, or sets ofinstructions; and a processor (not shown) to execute the system 130. Thememory may be any system or device including non-transitory computerreadable media for placing, keeping, and/or receiving information (e.g.,RAM, ROM, EEPROM, flash memory, optical disc storage, magnetic storage,etc.). In some configurations, the host 150 may be a portable handheldtool, including a touch interface, for example. Further, in someinstances, the system 130 is an application-specific integrated circuit(ASIC). While FIG. 1 shows the host 150 as including a display, in someinstances the host 150 does not include a display.

The integrated diagnostics system 130 performs online diagnostics,offline diagnostics, and/or an integrated diagnostics analysis on acontrol valve (as noted, one or more of the field devices 15-22 and40-46 may be a control valve). As shown, the host 150 provides all ofthe functionality associated with the system 130. However, in someconfigurations the integrated diagnostics system 130 is a distributedsystem. For example, online diagnostics functionality of the diagnosticssystem 130 may be implemented by a valve controller for a control valve,and the offline diagnostics functionality and integrated diagnosticsanalysis functionality may be implemented by a host communicativelyconnected to the data highway 10. In this implementation, the valvecontroller may transmit collected diagnostics data (e.g., via the I/Ocard 26 or 28 and the data highway 10) to the host 150 where theintegrated diagnostics analysis is performed.

It is noted that although FIG. 1 only illustrates a single controller 11with a small number of field devices 15-22 and 40-46, wireless gateways35, wireless adaptors 52, access points 55, routers 58, and wirelessprocess control communications networks 70 included in the exampleprocess plant 5, this is only an illustrative and non-limitingembodiment. Any suitable number of controllers 11 may be included in theprocess control plant or system 5, and any of the controllers 11 maycommunicate with any number of wired or wireless devices and networks15-22, 40-46, 35, 52, 55, 58 and 70 to control a process in the plant 5.This system could be integrated as local analytics, edge basedanalytics, or remote analytics performed in the Cloud.

II. An Example Control Valve that May be Diagnosed and Analyzed by theIntegrated Diagnostics System 130

FIG. 2 is a conceptual block diagram depicting the integrateddiagnostics system 130 (also shown in FIG. 1) communicatively connectedto a control valve 213, which is part of a single-input, single-outputprocess control loop 210. The integrated diagnostics system 130 collectsinformation from the control valve 213 and various sensors, and usesthis information to perform online diagnostics, offline diagnostics,and/or an integrated analysis of diagnostics data resulting from theonline and offline diagnostics, enabling the integrated diagnosticssystem 130 to track the behavior and health of the control valve 213.The components of the control loop 210 are described below, followed bya discussion of the system 130 and its interactions with the componentsof the control loop 210.

In addition to the control valve 213, the control loop 210 includes atransmitter 222, summing junction 224, and a controller 212. The controlvalve 213 can operate in the plant 5 shown in FIG. 1, and may be similarto one or more of the field devices 15-22 or 40-46. For example, thecontrol valve may be communicatively connected to the data highway 10via the I/O devices 26 or 28, the controller 11, and/or the gateway 35.In normal operation, the process controller 212 controls the controlvalve 213 to manipulate a process variable of a process 220. Toimplement control of the valve 213, the controller 212 sends, forexample, a 4 to 20 mA command signal to the control valve 213. Thecontrol valve 213 is illustrated as including a positioner 214 (whichmay be a current-to-pressure (I/P) transducer) that typically sends a 3to 15 psig pressure signal to a valve actuator 215 (e.g., a pneumaticrelay and/or an actuator) which, in turn, pneumatically controls acontrol element 218 (e.g., a plug) with a pressure signal (air). Byadjusting the control element 218, flow through the control valve 213can be controlled, enabling control of a process variable within theprocess 220 (e.g., a fluid level in a tank, a flow level in a pipe, atemperature or pressure of a material, etc.).

As is standard, a transmitter 222 measures the process variable of theprocess 220 and transmits an indication of the measured process variableto a summing junction 224. The summing junction 224 compares themeasured value of the process variable (converted into a normalizedpercentage) to a set point to produce an error signal indicative of thedifference. The summing junction 224 then provides the calculated errorsignal to the process controller 212. The set point, which may begenerated by a user, an operator or another controller is typicallynormalized to be between 0 and 100 percent and indicates the desiredvalue of the process variable. The process controller 212 uses the errorsignal to generate the command signal according to any desired techniqueand delivers the command signal to the control valve 213 to therebyeffect control of the process variable.

While the control valve 213 is illustrated as including the positioner214, the actuator 215 and the control element 218, the control valve 213may include any other type of valve mechanisms or elements instead of orin addition to those illustrated in FIG. 1 including, for example, anelectro-pneumatic positioner having an I/P unit integrated therein. Asanother example, the actuator 215 may be spring-based, and may exert amechanical force on the control element 218 in response to the pressuresignal received from the positioner 214. Additionally, anelectro-pneumatic positioner may also integrate an array of one or moresensors, and/or a memory, and/or a parameter estimation unit therein.Furthermore, it should be understood that the control valve 213 may beany other type of device (besides a valve controlling device) thatcontrols a process variable in any other desired or known manner. Thecontrol valve 213 may be, for example, a damper, etc.

As noted, the integrated diagnostics system 130 collects data fromvarious devices in the loop 210 and utilizes the collected data toestimate various loop parameters (friction, dead time, dead band, etc.)and to perform online and offline diagnostics. One or more components ofthe system 130 may be implemented by the host 150 (e.g., a serverconnected to the various sensors via the data highway 10, a portabletool directly or indirectly connected to the various sensors, etc.). Insome configurations, one or more components of the integrateddiagnostics system 130 can be internal to the control valve 213 or anyother process control device (e.g., field device) in a process controlnetwork. If the control valve 213 is a micro-processor based device, theintegrated diagnostics system 130 can share the same processor andmemory as that already within the control valve 213. Thus, it iscontemplated that a statistical analysis (e.g., for the onlinediagnostics, offline diagnostics, or integrated analysis) may beperformed in the device in which the measurements are made (such as inany field device) with the results being sent to a user display or to ahost device (e.g., the host 150) for use or, alternatively, the signalmeasurements may be made by a device (such as a field device) with suchmeasurements then being sent to a remote location (such as the host 150)where the statistical analysis is performed. In any event, regardless ofthe precise nature of the system 130, it collects via various sensorsdata pertaining to the valve 213.

For example, the integrated diagnostics system 130 may detect one ormore of the command signals delivered to the positioner 214 using acurrent sensor 232, the pressure output from the positioner 214 using apressure sensor 234, the actuator command signal output by the actuator215 using a pressure sensor 236, and the valve position at the output ofthe control element 218 using a position sensor 237. If desired, theintegrated diagnostics system 130 may also or alternatively detect theset point signal, the error signal at the output of the summing junction224, the process variable, the output of the transmitter 222 or anyother signal or phenomena that causes or indicates movement or operationof the control valve 213 or process control loop 210. It should also benoted that other types of process control devices may have other signalsor phenomena associated therewith that may be used by the integrateddiagnostics system 130.

As will be evident, the integrated diagnostics system 130 may also readan indication of the controller command signal, the pressure signal, theactuator command signal, or the valve position when the control valve213 is configured to communicate those measurements. Likewise, theintegrated diagnostics system 130 may detect signals generated by othersensors already within the control valve 213, such as the valve positionindicated by the position sensor 237. Of course, the sensors used by theintegrated diagnostics system 130 can be any known sensors and may beeither analog or digital sensors. For example, the position sensor 237may be any desired motion or position measuring device including, forexample, a potentiometer, a linear variable differential transformer(LVDT), a rotary variable differential transformer (RVDT), a Hall effectmotion sensor, a magneto resistive motion sensor, a variable capacitormotion sensor, etc. It will be understood that, if the sensors areanalog sensors, the integrated diagnostics system 130 may include one ormore analog-to-digital converters which samples the analog signal andstores the sampled signal in a memory within the integrated diagnosticssystem 130. However, if the sensors are digital sensors, they may supplydigital signals directly to the integrated diagnostics system 130 whichmay then store those signals in memory in any desired manner. Moreover,if two or more signals are being collected, the integrated diagnosticssystem 130 may store these signals as components of data pointsassociated with any particular time. For example, each data point attime T1, T2, . . . Tn may have an input command signal component, apressure signal component, an actuator travel signal component, etc. Ofcourse, these data points or components thereof may be stored in memoryin any desired or known manner.

As shown in FIG. 1, the integrated diagnostics system 130 includes adiagnostics module 247 and an integrated diagnostics analyzer 249, eachof which may take any desirable form, including software, firmware,hardware, etc. For example, each of the components 247 and 249 may be amodule, application, or a set of instructions stored to a memory of acomputing device and executable by a processor of the computing device.

The integrated diagnostics system 130 may implement the diagnosticsmodule 247 to perform offline diagnostics on the control valve 213.Generally speaking, during offline diagnostics, the control valve 213 istaken offline. The system 130 then controls the valve 213, driving thethrottling element of the valve 213 through its full range of travel. Asthe valve 213 is opening or closing, the system 130 collects data fromone or more of the sensors 232-237 and uses the collected data togenerate an offline valve signature (e.g., stored as offline signaturedata). For example, an offline valve signature can include a set ofexpected sensor measurements corresponding to a set of respectivepositions of the valve 213. As a more specific example, the offlinevalve signature can specify how measurements from the pressure sensor214 relate to measurements from the position sensor 237, thus relatingpressure exerted on the actuator 215 to the position of the actuator 215and/or to the position of the control element 218.

Further, the integrated diagnostics system 130 may implement thediagnostics module 247 to perform online diagnostics on the controlvalve 213. During online diagnostics, the system 130 collects data fromone or more of the sensors 232-237 and uses the collected data togenerate an online valve signature (e.g., stored as online signaturedata). Similar to an offline valve signature, an online valve signaturecan include a set of expected sensor measurements corresponding to a setof respective positions of the valve 213. Notably, when performingonline diagnostics, the integrated diagnostics system 130 does notrequire the control valve 213 be taken offline or out of the normaloperating environment. Rather, the system 130 collects data while thevalve 213 is controlled by the controller 212 during normal onlineoperation. As a result, the online valve signature may correlated sensormeasurements to valve positions over a more limited range. For example,unlike an offline signature which may relate sensor measurements tovalve positions for a range of 0% open to 100% open, an online signaturemay relate sensor measurements to valve positions for a range that ittypically experiences during normal online operation, such as 40% opento 60% open.

The system 130 in general may implement the integrated diagnosticsanalyzer 249 to analyze an current operating data, an online valvesignature, and offline valve signature, and may rely on that analysis toestimate a behavior or health of the valve. Example techniques that maybe implemented by the analyzer 249 are discussed below with reference toFIGS. 5 and 6.

III. An Example Valve Controller that can Implement DiagnosticsFunctions

FIG. 3 illustrates an example digital valve controller (for simplicity,“controller”) 300 capable of controlling a valve 302 and implementingdiagnostics functions 347, which may be similar to the diagnosticsmodule 247 shown in FIG. 2. The valve 302 and controller 300 may bereferred to as a “smart valve” or “smart field device,” and may besimilar to one or more of the field devices 15-22 or 40-46 shown inFIG. 1. The controller 300 may be communicatively connected to the datahighway 10 shown in FIG. 1 via the I/O devices 26 or 28, the controller11, and/or the gateway 35.

As discussed below, the controller 300 is capable of fast, dynamic insitu process control for various types of process variables, performanceoptimization, real-time diagnostics, etc. By implementing PID controldirectly at a valve or another field device, the controller 300 candeliver improved loop performance. Moreover, the controller 300effectively replaces several devices, thereby simplifying installationand maintenance. A single supplier can provide the controller 300 fortotal loop control.

In the example configuration of FIG. 3, the controller 300 operates onthe valve 302, which is installed in a pipeline 304. The valve 302 andthe pipeline 304 can be similar to the valve 213 discussed above withreference to FIG. 2. The controller 300 includes function modules 310, amemory 312 and a pneumatic output module 314 (which may be similar tothe actuator 215 shown in FIG. 2). In some implementations, thecontroller 300 also can include a sensor, such as a pressure sensor 316.Further, the integrated controller 300 can include a network interfacemodule 318. In an example implementation, the components 300-322 arecoupled to a backplane 324. The controller 300 can receive a setpointfor a process variable and configuration data via a communication line350, and provide process information and reports to a remote host via acommunication line 352. The lines 350 and 352 are not necessarilyphysically separate channels, and in general can be communicationchannels on a same wire or a set of wires, different radio channels ordifferent timeslots of a same channel, or any other suitable types ofphysical or logic channels. The lines 350 and 352 may be communicativelyconnected to a data highway, such as the data highway 10 shown in FIG.1.

Next, the components 310-324 are briefly considered individually,followed by a discussion of operation of the controller 300.

Depending on the implementation, the function modules 310 can include ageneral-purpose central processing unit (CPU) configured to executeinstructions stored in the memory 312 and/or one or severalspecial-purpose modules, such as application-specific integratedcircuits (ASICs) configured to execute PID functions. The CPU caninclude a real-time clock accurate to within a certain number of minutes(e.g., 10) per year over the entire range of temperatures at which thecontroller 300 can operate. More generally, the function modules 310 caninclude one or more processors of any suitable type. As schematicallyillustrated in FIG. 3, the function modules 310 can implement one orseveral PID functions 360, one or several tuning functions 362, one orseveral real-time positioning functions 364, the online diagnosticsmodule 247 discussed with reference to FIG. 2, and, if desired,additional functions related to monitoring, troubleshooting, processvariability optimization, etc. The function modules 310 can implementthese functions in hardware, firmware, software instructions executableby one or more processors, or any suitable combination of hardware,firmware, and software.

In an example scenario, the function modules 310 receives a pressuresetpoint via a communication line 350 for the pipeline 304 from a remotehost via the network interface 318, receives sensor data from thepressure sensor 316, executes a PID algorithm to generate a positioningcommand (or, more generally, an output signal), and applies thepositioning command to the valve 302 via the pneumatic output module314. It is noted that the function modules 310 can receive a setpointfor a process variable rather than for a field device. The functionmodules 310 can retrieve the tuning parameters for the PID loop from thememory 312. These parameters can be pre-configured, received from aremote host, determined and/or adjusted used auto-tuning, etc., asdiscussed in more detail below. Thus, the function module 310 can uselocally collected sensor data to locally, without relying on a remotehost, execute control functions. Depending on the implementations, thefunction modules 310 can implement functions to control many differentprocess variables, such as pressure, position, temperature, flow rate,or pH.

More generally, the function modules 310 allow the integrated controller300 to quickly and efficiently react to device issues (e.g., detect aproblem with the valve 302, detect failure of the sensor 316), controlloop issues (e.g., determine that PID parameters should be adjusted),carry out emergency procedures (e.g., shut down flow through thepipeline 304), generate alerts for output via the local UI module 322and/or for reporting to a remote host.

The memory 312 can be any suitable non-transitory computer-readablemedium and can include volatile and/or non-volatile components. Thus,the memory 312 can include random-access memory (RAM), a hard disk, aflash drive, or any other suitable memory components. The memory 312 canstore PID parameters 370, online diagnostics data 372, valve signaturedata 374, and process signature data 376. In particular, the PIDparameters 370 can specify proportional, derivate, and integral gainvalues for a loop controlling the valve 302 or another field device. ThePID parameters 370 can be provided configured by a remote operator via aremote host and provided via the network interface 318, a local operatorvia the UI module 322, pre-stored in the memory 312 by the manufacturerof the integrated controller 300, etc. In some scenarios, the integratedcontroller 300 can adjust PID parameters 370 in response to receiving anew setpoint 350 or upon conducting diagnostics, for example.

The valve signature data 374 and the process signature data 376 candescribe expected behavior of the valve 302 and the loop for controllingthe valve 302, respectively. Generally speaking, signatures stored inthe memory 312 can describe the expected response of a sub-system toinput signals, for comparing to the actual response of the sub-systemand determining whether the sub-system operates properly. The signaturesstored in the memory 312 may include online signatures such as thosedescribed with reference to FIG. 2.

The integrated controller 300 can locally collect data for determiningthe actual response to a sub-system such as the valve 302 and againlocally compare the collected data to the signature 374, the signature376, or another signature. In this manner, the integrated controller canquickly and efficiently detect valve problems (e.g., actuator beingstuck, pressure loss, leakage of fluid), process upsets, control loopdegradation, etc. Further, if desired, the integrated controller 300 canexecute the appropriate tuning function 362 to create a processsignature. Using the process signature, the controller can detect asuitable set of tuning parameters for the desired control loop response.

Further, the memory 312 can retain configuration information, logs,history data, status of input and output ports, etc. The integratedprocess controller 300 can be configured to retain in the memory 312 anevent log, an alert log, real-time clock data, a loop log, historicaldata, database data, status of input/output channels, function moduleattributes, user lists, etc., in the event of a power failure.

With continued reference to FIG. 3, the pneumatic output module 314 canactuate the valve 302 during operation. The pneumatic output module 314can include an I/P transducer and one or more relay components. In anexample implementation, the pneumatic output module 314 includes an I/Pmodule and a double-acting relay. Further, in one implementation, thepneumatic output module 314 includes a relay that bleeds and one thatlocks in the last value in the event of a power failure. The controller300 can provide indications of output pressure of the pneumatic outputmodule 314 via the local UI 322 or the RUI of a remote host. It is notedthat the controller 300 can monitor operation of the pneumatic outputmodule 314 by sensing output pressure, for example, and performreal-time online diagnostics to detect complete or partial failureearly.

When used in applications in which natural gas is the medium, thecontroller 300 can include one or several no-bleed pneumatic componentsto comply with emission regulations. The controller 300 in theseimplementations allows continued use of the medium while reducing theemissions compared to traditional pneumatic devices.

In an example implementation, the pressure sensor 316 is an integralpressure sensor module configured to measure pressure as the processvariable (PV). The pressure sensor 116 may bolt directly to the housing330. In alternative implementations, however, the pressure sensor 316can be provided as a separate device coupled to the controller 300 by awired link or a short-range wireless link. Similar to the pneumaticoutput module 314 discussed above, the controller 300 can display livedata for the pressure sensor 316 via a local UI module (not shown) orthe RUI at the remote host. Further, the controller 300 can supportcommands using which an operator can request, or pull, live data via thelocal or remote interface.

Although the example implementation depicted in FIG. 3 includes apressure sensor 316 integral with the remaining assembly of thecontroller 300, in other implementations the controller 300 can includeadditional I/O modules such as a valve position sensor or a temperaturesensor. These and other modules can be inserted into the backplane 324,or the controller 300 can communicate with the additional modules viashort-range communication links.

The network interface module 318 can support general-purpose protocolssuch as the Internet Protocol (IP) as well as special-purpose processcontrol and industrial automation protocols designed to convey commandsand parameters for controlling a process plant, such as Modbus, HART,Profibus, etc. The network interface module 318 can support wired and/orwireless communications. As discussed above, the controller 300 canreceive a setpoint value from a remote host via a long-rangecommunication link to which the network interface module 388 is coupled.The network interface module 318 can support Ethernet ports and, in someimplementations, implement protection against unauthorized access.

The backplane 324 can be a component with no active circuitry, residingin the housing 330 and having connections for mounting various modules.As illustrated in FIG. 3, the backplane 324 can interconnect thefunction modules 310, the memory 312, the network interface 318, thepneumatic output module 314, etc. The backplane 324 in general caninclude connections to receive power, select lines, communication ports,etc. In some implementations, the CPU module is selected or designed soas to prevent mis-insertion into the backplane 324.

In operation, the controller 300 can perform real-time prognostics toallow operators to quickly gain accurate insight into process changes,issues related to the valve 302, transmissions and communications,control maintenance, etc. Thus, the controller 300 can carry out controlfunctions in the field. In other words, rather than operating based oncommands generated by a remote host that implements a PID loop, thecontroller 300 can control the valve 302 and/or loop parameters locallyand, if desired, report information to a host via a communicationnetwork via the communication line 352.

Further, although the controller 300 can receive the setpoint value 350via a wireless communication link, which may introduce a communicationdelay, the controller 300 then can drive the process variable to thesetpoint using wired signaling between components within the samedevices, or even on-chip signaling. More specifically, the controller300 need not report pressure, position, temperature, level, flow rate,or other measurements to another device capable of calculating newcontrol signals. Updates to the setpoint therefore may be limited by thespeed of wireless communications, but communications between sensors,modules calculating proportional, derivate, and integral values, etc.occur at higher speeds.

IV. Example Plots that May be Generated and Analyzed by the IntegratedDiagnostics System 130

FIG. 4 illustrates an example plot 400 of actuator pressure versus valveposition for a typical sliding stem valve, generated by the integrateddiagnostics system 130 performing online diagnostics. The plot 400 mayalso be referred to as an online valve signature. Each point in the plot400 corresponds to a concurrent measurement obtained by the integrateddiagnostics system 130 of pressure exerted on the actuator 215 shown inFIG. 2 (i.e., “actuator pressure”) and a position of the actuator 215 orcontrol element 218 shown in FIG. 2 (i.e., “valve position”). While theplot 400 is discussed with reference to the valve 213 shown in FIG. 2,it may be implemented with respect to any suitable valve.

The plot 400 corresponds to a single cycle of operation of the valve213. This single cycle of operation may be referred to as an “onlinesignature” for the valve 213. The system 130 may collect multiple onlinesignatures. In some instances, the system 130 may generate an onlinesignature based on a full cycle, a partial cycle (e.g., representing atrend across two data points, three data points, etc.), or may generatean online signature based on multiple cycles, representing an averagecycle over a given period of time or a certain number of cycles, ratherthan a single cycle (e.g., the online signature may be a rolling averageof the past ten online signatures).

Those of ordinary skill in the art will appreciate that upon a reversalof direction by the valve 213, the control element 218 operates througha friction zone in which the applied pressure increases or decreases asignificant amount with little or no resulting movement of the controlelement 218. This friction zone, which is caused by friction within thevalve 213, is generally indicated by the more vertical lines 410 in FIG.4. Upon exiting the friction zone, the control element 218 then moves asignificant amount with relatively little change in the appliedpressure. This operation is generally indicated by the more horizontallines 414 in FIG. 4. Of course, other methods of representing therelationship between actuator pressure and actuator or control elementposition are also available. For example, actuator pressure and actuatorposition can be plotted separately versus time. By aligning the tworesulting plots along the same timeline, the plots can be simultaneouslyanalyzed to detect the amount of pressure required to enable themovement of the actuator 215 and/or control element 218. Thus, one ofordinary skill in the art will appreciate that the exemplary plotsdiscussed herein are presented by way of illustration only.

FIG. 5 illustrates an example plot 500 of actuator pressure versus valveposition, generated by the integrated diagnostics system 130 performingan integrated diagnostics analysis that utilizes both online and offlinediagnostics. The plot 500 includes an offline signature 502, an onlinesignature 504, data points 506, trend lines 508 and 510, and ameasurement 512 of a diagnostic metric.

The offline signature 502 is generated by taking the valve offline,controlling the valve through a full range of travel, and collectingdata over time pertaining to pressure exerted on a valve actuatorcompared to travel or position of the control element of the valve. Inother words, the system 103 collects data so that at multiple discreetpoints in time, pressure can be compared to valve position. Because thevalve is typically taken through a full range of motion during offlinediagnostics testing, these relationships can be observed for the fullrange of the valve. Utilizing the collected data, the system 130 cangenerate the offline valve signature 502. In short, this represents thetypical behavior of the valve when the valve is being stroked. Dependingon the embodiment, the offline signature may be based on a partial cycle(e.g., 0% to 100% open, but not vice versa), a full cycle, or multiplecycles (e.g., representing an average of the multiple cycles).

The online diagnostics signature 504 may be similar to the onlinesignature discussed with reference to FIG. 4. In short, the system 130generates the online signature by observing the valve operate over timeunder normal operating conditions. In contrast to the offline signature,which is usually generated based on data collected while the valve movesthrough a full range of travel, the online signature is often generatedbased on data collected while the valve moves through a more limitedrange of travel because the valve may be configured to typically onlymove through that limited range of travel during normal operation.

The plot 500 further includes current data points 506. Generallyspeaking, the system 130 collects the current data points 506 duringnormal operation of the valve and utilizes the current data points 506to generate or identify an online valve signature such as the signature504. In some instances, the current data points 506 may be compared toprevious online valve signatures. For example, FIG. 5 shows data points506 above the signature 504, indicating that, for the valve positionsassociated with these data points 506, the valve required more pressurethan expected or observed based on the online signature 504. Similarly,the plot 500 shows three data points 506 below the online signature 504,indicating that at certain points the valve required less pressure for agiven position.

Finally, the plot 500 includes trend lines 508 and 510 that aregenerated by the system 130 from the current data points 506. The system130 can generate the trend lines 508 and 510 and analyze these lines toevaluate the health of the valve. In some instances, the trend lines 508and 510 may be part of an online valve signature, or may themselvesrepresent an online valve signature (in this case, an incomplete valvesignature).

The trend lines 510 and 508 can be compared to the online signature 504and offline signature 502 to evaluate the health of the valve. Becausethe trend lines 510 and 508 can be compared to both an online signatureand offline signature, the system 103 can better evaluate the health ofthe valve when compared to other diagnostic systems.

For example, if one were to compare the trend line 510 to the offlinesignature 502 alone (something often done in typical diagnosticevaluations), one would observe that an excessive amount of pressure isrequired to move the valve to a given position (relative to the offlinesignature), and might thus conclude that the valve is behaving in anabnormal manner. Similarly, one could compare the trend line 510 to theonline signature 504 alone and conclude that the valve is requiring lesspressure to move, and might consequently conclude that the valve isbehaving abnormally. However, an analysis of the trend line 510 in lightof the signature 502 and signature 504 reveals that, for a given valveposition, the valve actuator requires pressure within an expected rangewhen both the online signature 504 and offline signature 502 areconsidered.

The plot 500 also shows a measurement 512 of a diagnostic metric. Thisparticular metric is a pressure differential that reveals the size ofthe friction zone associated with the valve. In short, the measurement512 is of a difference between: (i) a pressure measured for a valveposition as the valve is opening, and (ii) a pressure measured for thatsame valve position as the valve is closing. The measurement 512 revealsa level of friction associated with the valve. As already noted withreference to FIG. 4, a valve operates through a friction zone in whichthe applied pressure increases or decreases a significant amount withlittle or no resulting movement of the valve. This friction zone, whichis caused by friction within the valve, is generally indicated by themore vertical lines of the offline signature 502 and the onlinesignature 504. Upon exiting the friction zone, the valve then moves asignificant amount with relatively little change in the appliedpressure. This zone of easier movement is represented by the morehorizontal lines of the offline signature 502 and the online signature504. The measurement 512 reveals the size of the friction zone.

The integrated diagnostics system 130 can identify, from the data points506, a current friction zone measurement (not show), which can becompared to the measurement 512 and/or to a measurement of a frictionzone associated with the online signature 504. Thus, the integrateddiagnostics system 130 can determine whether the current friction zoneis near the friction zone of the signatures 502 and 504. Further, thesystem 130 can monitor the friction zone over time to determine whetherthe friction zone is increasing or decreasing (either of which mayindicate a problem with the health of the valve), and a rate at whichthe friction zone is increasing or decreasing.

The integrated diagnostics system 130 can similarly observe otherdiagnostic metrics. For example, the integrated diagnostics system 130can monitor the slope of the more horizontal lines of the offlinesignature 502, the offline signature 504, and/or trends 508 and 510.This slope generally correlates to a spring rate associated with thevalve. Thus, the system 130 can monitor these slopes and determinewhether the slope is increasing or decreasing over time (which, again,may indicate a problem with the health of the valve).

V. An Example Method of Performing Integrated Diagnostics Analysis

FIG. 6 is a flow chart depicting an example method 600 of performingintegrated diagnostics analysis. The method 600 may be implemented, inwhole or in part, by the integrated diagnostics system 130 shown inFIG. 1. Software instructions that implement the method 600 may be savedin a non-transitory, computer-readable memory. While the method 600 isdiscussed with reference to the valve 213 shown in FIG. 2, in generalthe method 600 can be applied to any suitable valve.

The method 600 can be implemented to evaluate the stability of a valveover time. In short, offline and online behaviors of the valve areobserved and compared to each other. This relationship is observed overtime. The system 130 can generate an alarm when the relationship beginsto change, indicating that the behavior of the valve is beginning tochange when compared to historic performance.

At block 602, the system 130 collects offline diagnostics data. Asalready noted, this generally involves taking the valve 213 offline,stroking the valve 213 through its entire range of travel, andcollecting (e.g., via the sensors 232-237) diagnostics data as the valve213 is moving. In some instances, the diagnostics data includes atimestamp generated by a clock (e.g., an internal hardware or softwareclock of the host 150 shown in FIG. 1 or of the valve controller 300shown in FIG. 3). Once this diagnostics data has been collected, thesystem 130 can generate an offline signature such as the signature 502shown in FIG. 5.

At block 604, the system 130 calculates an offline response from theoffline diagnostics data and/or offline signature (T_(R-OFF)). In short,the offline response represents a response by an output variable (e.g.,the valve 213 in this case) to a change in an input variable duringoffline diagnostics testing. Generally speaking, the input variable isthe pressure applied to the actuator 215 or the pressure applied byactuator 215 to the control element 218, and the output variable is theresponse time (e.g., the time it takes for the control element 218 tomove and reach a steady state). In some instances, the output variableis the position at which the control element 218 reaches at steady state(e.g., 60% open) after responding to the change in the input variable.In some configurations, the input variable could be the 4-20 commandreceived by the positioner 214.

At block 606, the system 130 collects online diagnostics data. Theonline diagnostics data is data collected (e.g., via one or more of thesensors 232-237) during online operation of the valve 213. While theonline diagnostics data is being collected, the controller 212 typicallycontrols the valve 213 as it normally would to implement the controllogic of the process 220.

At block 608, the system 130 calculates an online response from theonline diagnostics data (T_(R-ON)). Generally speaking, the onlineresponse represents a response by an output variable (e.g., the valve213 in this case) to an input variable during online operation. Like theoffline response, the online response may relate a response of any givenoutput variable (e.g., measured by one of the sensors 234-237) to amanipulation of any other input variable (e.g., measured by one of thesensors 232-236 and/or a clock). That said, the input and outputvariables utilized for the calculated online response are generally thesame input and output variables that were utilized when calculating theoffline response. For example, if the offline response utilizes as aninput variable a pressure signal applied on the actuator 215 andutilizes as an output variable the position of the control element 218(as measured by the sensor 237) responding to changes in the pressuresignal, the online response similarly utilizes the pressure signal andcontrol element position as the input variable and output variable,respectively.

At block 610, the system 130 calculates a response ratio based on thecalculated online and offline responses (e.g., T_(R-ON)/T_(R-OFF)). Forexample, if during online operation the valve 213 takes three seconds torespond to a given pressure applied to the actuator 215 and the offlinesignature indicates that the valve 213 took two seconds to respond tothat same pressure, the response ratio is 1.5 (3/2). Alternatively, ifthe valve takes two seconds to respond to the given pressure, theresponse ratio is 1 (2/2).

Generally speaking, the response ratio indicates how closely the onlinebehavior of the valve 213 mimics the behavior of the valve 213 observedduring offline diagnostics testing. In some instances, it is expectedthat online performance of the valve differs from performance duringoffline diagnostics testing. This could be caused by a number offactors, such as wear and tear on the valve since offline diagnosticstesting was performed, changes in process conditions, changes inenvironmental conditions, etc. Consequently, a response ratio valuegreater or less than one does not necessarily suggest the valve isexperiencing a problem.

At block 612, the system 130 analyzes the rate-of-change of the responseratio over time. For example, the system 130 may estimate a line of bestfit by evaluating the response ratio value for each of the last tenonline responses that have been calculated. With reference to theprevious example, the last ten online response might be (3, 3, 3, 3,3.1, 3.2, 3.3, 3.7, 4, 4.5), meaning the corresponding values for theresponse ratio would be (1.5, 1.5, 1.5, 1.5, 1.55, 1.6, 1.65, 1.85, 2,2.25). As can be seen, the response ratio is relative stable for thefirst five or six samples, but then progressively increases over thelast five or six samples. This could indicate the behavior of the valveis becoming unstable, suggesting a potential problem with the valve.

As noted above, it is sometimes expected that online performance of thevalve differs from offline performance. The system 130 can account forthis expected difference in online and offline behavior by observing thetrend of the response ratio over time. This trend or rate of changeindicates whether the relationship between the offline response and theonline response remains stable over time. That is, the offline andonline responses may differ, but so long as the response ratio betweenthe two remains relatively stable, the valve is likely in goodcondition. Said another way, a small or nonexistent rate of change ofthe response ratio indicates that the monitored valve 213 is exhibitingrelatively consistent behavior over time. For example, a rate of changenear zero may indicate that, relative to past performance, the valve 213is opening or closing to expected positions in an expected amount oftime in response to a given pressure exerted on the actuator 215. Thus,when the rate of change does not exceed a threshold, which may be anysuitable value (e.g., 2), the system 130 continues collecting onlinedata (block 606).

However, if the rate of change of the response ratio exceeds a threshold(e.g., 2), this indicates that the valve is deviating further andfurther from past performance. Consequently, if the rate of changeexceeds a threshold, an alarm is generated (block 614). Depending on theconfiguration, the alarm can be visual or audible in nature. The alarmcan be displayed or sounded at an operator display, a display for avalve controller, etc.

VI. Additional Remarks

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“identifying,” “presenting,” “displaying,” or the like may refer toactions or processes of a machine (e.g., a computer) that manipulates ortransforms data represented as physical (e.g., electronic, magnetic, oroptical) quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

When implemented in software, any of the described applications,services, engines, routines, and modules may be stored in any tangible,non-transitory computer readable memory such as on a magnetic disk, alaser disk, solid state memory device, molecular memory storage device,an optical disk, or other storage medium, in a RAM or ROM of a computeror processor, etc. Although some example systems are disclosed asincluding, among other components, software and/or firmware executed onhardware, it should be noted that such systems are merely illustrativeand should not be considered as limiting. For example, it iscontemplated that any or all of these hardware, software, and firmwarecomponents could be embodied exclusively in hardware, exclusively insoftware, or in any combination of hardware and software. Accordingly,persons of ordinary skill in the art will readily appreciate that theexamples provided are not the only way to implement such systems.

What is claimed is:
 1. A method comprising: actuating a control valvevia a first control signal; receiving, by one or more processors,offline diagnostics data for the control valve, the offline diagnosticsdata describing a first relationship between pressure and valve positionobserved during a response of the control valve to the first controlsignal for a first range of travel when the control valve is not inservice in a process plant; calculating an offline response of thecontrol valve utilizing the offline diagnostics data; actuating thecontrol valve via a plurality of control signals; receiving, by the oneor more processors, online diagnostics data for the control valve, theonline diagnostics data describing a plurality of relationships betweenpressure and valve position observed during a plurality of responses ofthe control valve to the plurality of control signals for one or moreranges of travel, each less than the first range of travel, when thecontrol valve is in service in the process plant; calculating aplurality of online responses for the control valve utilizing the onlinediagnostics data; for each of the plurality of online responses,calculating a value for a response ratio relating the offline responseto one of the plurality of online responses such that each onlineresponse has a corresponding value for the response ratio; analyzing thevalues of the response ratio to determine a rate of change for theresponse ratio over time; and determining that the rate of change forthe response ratio exceeds a threshold value; and in response todetermining that the rate of change for the response ratio exceeds thethreshold value, generating an indication to be provided to an operatorvia a user interface.
 2. The method of claim 1, wherein the offlinediagnostics data represents an offline signature and wherein the onlinediagnostics data represents an online signature.
 3. The method of claim2, wherein the offline signature and the online signature each relatepressure measurements to valve position measurements, wherein thepressure measurements are measurements of pressure applied to anactuator of the control valve and the valve position measurements aremeasurements of the control valve's position after responding to theapplied pressure.
 4. The method of claim 1, wherein the one or moreprocessors include a processor of a portable handheld tool.
 5. Themethod of claim 1, wherein the diagnostic metric is a differential inpressure measurements corresponding to valve friction, the pressuremeasurements being (i) measurements of pressure applied to an actuatorof the control valve or (ii) measurements of pressure applied to acontrol element of the control valve.
 6. The method of claim 1, whereinthe diagnostic metric is a slope corresponding to a spring rate.
 7. Asystem comprising: a control valve in a process plant; a plurality ofsensors configured to monitor the control valve; and an integrateddiagnostics system communicatively connected to the plurality ofsensors, the diagnostics system configured to: receive, via theplurality of sensors, offline diagnostics data for the control valve,the offline diagnostics data describing a first relationship betweenpressure and valve position observed during a response of the controlvalve to a first control signal for a first range of travel when thecontrol valve is not in service in the process plant; calculate anoffline response of the control valve utilizing the offline diagnosticsdata; receive, via the plurality of sensors, online diagnostics data forthe control valve, the online diagnostics data describing a plurality ofrelationships between pressure and valve position observed during aplurality of responses of the control valve to a plurality of controlsignals for one or more ranges of travel, each less than the first rangeof travel, when the control valve is in service in the process plant;calculate a plurality of online responses for the control valveutilizing the online diagnostics data; for each of the plurality ofonline responses, calculate a value for a response ratio relating theoffline response to one of the plurality of online responses such thateach online response has a corresponding value for the response ratio;analyze the values of the response ratio to determine a rate of changefor the response ratio over time; and determine that the rate of changefor the response ratio exceeds a threshold value; and generate, inresponse to determining that the rate of change for the response ratioexceeds the threshold value, an indication to be provided to an operatorvia a user interface.
 8. The system of claim 7, wherein the integrateddiagnostics system is implemented by one or more of the following: aserver communicatively connected to the plurality of sensors and acontroller configured to control the control valve; a digital valvecontroller configured to control the control valve; and a portablehandheld tool configured to wireless communicate with one or more of theserver and the digital valve controller.
 9. The system of claim 7,wherein the plurality of sensors includes: a pressure sensor monitoring:(i) a pressure applied on an actuator of the control valve, or (ii) apressure applied on a control element of the control valve; and aposition sensor monitoring a position of the control element of thecontrol valve.
 10. The system of claim 7, wherein the offlinediagnostics data and the online diagnostics data each include: (i)pressure measurements obtained by the pressure sensor, and (ii) positionmeasurements obtained by the position sensor, each position measurementcorresponding to one of the pressure measurements.
 11. The system ofclaim 7, further including a clock, wherein the integrated diagnosticssystem is further configured to timestamp the offline diagnostics datawhen received and to timestamp the online diagnostics data whenreceived.
 12. The system of claim 11, wherein the offline diagnosticsdata and the online diagnostics data each include: (i) pressuremeasurements obtained by the pressure sensor, and (ii) response timescalculated using the clock, wherein each of the response timesrepresents a time it took the control valve to reach a steady stateafter responding to one of the pressure measurements.
 13. The system ofclaim 7, wherein the plurality of sensors includes: an electrical sensormonitoring a current signal received by the control valve; and aposition sensor monitoring a position of the control valve.
 14. A methodcomprising: initiating an offline diagnostics procedure on a controlvalve in a process plant, wherein the control valve is controlledthrough a first range of travel; collecting, during the offlinediagnostics procedure, offline diagnostics data from a plurality ofsensors monitoring the control valve; calculating an offline response ofthe control valve utilizing the offline diagnostics data; collecting,during online operation of the control valve during which the controlvalve is controlled through one or more ranges of travel each less thanthe first range of travel, online diagnostics data from the plurality ofsensors monitoring the control valve; calculating a plurality of onlineresponses for the control valve utilizing the online diagnostics data;for each of the plurality of online responses, calculating a value for aresponse ratio relating the offline response to one of the plurality ofonline responses; analyzing the values of the response ratio todetermine a rate of change for the response ratio over time; andgenerating an indication to be provided to an operator via a userinterface when the rate of change for the response ratio exceeds athreshold.
 15. The method of claim 14, wherein calculating the offlineresponse and calculating the plurality of online responses all comprise:calculating a position of the control valve as a function of a pressureasserted on a control element or an actuator of the control valve. 16.The method of claim 14, wherein calculating the offline response andcalculating the plurality of online responses all comprise: calculatinga response time of the control valve as a function of a pressureasserted on a control element or an actuator of the control valve. 17.The method of claim 1, further comprising: in response to determiningthat the rate of change for the response ratio exceeds the thresholdvalue, close the control valve.
 18. The system of claim 7, wherein thediagnostic system is further configured to close the control valve inresponse to determining that the rate of change for the response ratioexceeds the threshold value.